Point of View

Rapid automation (RA), also known as “robotics” and autonomics, is not a new technical development but has accelerated significantly since 2013. Better technology tools and operations clarity have enabled the automation of material parts of the repetitive work currently performed in shared service-type operations. However, there are limitations to robots’ usability and impact, namely, the type of transactions robots can perform and their limited value beyond efficiency in specific parts of the process. Despite that, the emergence of RA represents a valuable addition to Systems of EngagementsTM (SoE) forprocess operations and a useful complement to today’s systems of records. This paper describes the sphere of intervention for RA and recommends a more effective way to plan for its use.

What is RA?

Rapid automation (RA) technology, aka “robotics” and “autonomics,” mimics people interactions with user interfaces of ERPs, Microsoft Office documents, databases, etc. Technically speaking, RA interacts with different software systems at the GUI (graphical user interface) or presentation layer, the same level as a “human” user of the system. RA is a non-intrusive application with no need for integration with other systems and delivers productivity by replacing human effort. The time and cost involved in typical integration efforts between different software (the most common being workflow/ERP integration) are notorious pain points for operations and IT executives, and RA is a useful additional tool for those issues. Thus, RA is a non-intrusive application with no need for integration with other systems and delivers productivity by replacing human effort. It is a useful complement to the more traditional “system of records” technologies, primarily ERP.

Technically, most RA products are based on the well-understood Microsoft.net framework, with pre-built functions that make the development work fast-paced and relatively error-free. This also helps in making fast-paced revisions to existing code and reduces the effort required to extensively train developers on this technology.

RA’s sweet spot

To understand the ideal playground for RA, we have analyzed various processes across “horizontal” (e.g., Finance and Accounting) and industry “vertical” (operations in banking, insurance, etc.) functions. The technology can be applied across many processes and functions, it is scalable, and if the processing conditions are right, it can replace labor. Following are the best use cases for RA.

Dual data entry scenarios: Data manually entered in one system need not be reentered manually in any other system. RA replaces such dual human effort since invoices are indexed in the workflow and then manually reentered in ERP

Straight-through processing: Inputs arriving from various systems such as web pages for customer orders, workflow for invoices, emails, or Excel files must be entered into ERP. However, if the input is clean and the rules are well laid out, that data entry can be done through RA

Virtual “integration” between different systems: Standalone, legacy, ERP, or workflow systems often don’t “talk” to each other, and integrating them would cost millions of dollars and precious IT time. RA can provide lightweight integration connecting disparate systems at the user interface level as companies move to one global ERP backbone and retire legacy systems

Responding to data extraction and reporting requests: When data and report requests come from multiple process owners, vendors, and even end customers, employees log into a system to extract the data, format it, and send an email to the requestor. Since these requests are typically rule-based work, RA lends itself very well to such tasks

Rule-based decision-making: RA can execute decision-based tasks provided the rules driving those decisions are well laid out. For instance, on an invoice coming from a utility vendor, RA can change payment terms to “immediate” from whatever is on the invoice. If an order is above US$50k, RA would send it to a manager/approver for review, or if the price variance is less than 5%, or below a defined threshold, then RA would post the invoice. These are all rule-based scenarios that robotic software can execute

The potential impact of RA

Processes that have one or more of these characteristics can potentially see a productivity lift of anywhere between 10% and 50% or more if the conditions are particularly suitable. Broadly speaking, observations from our implementations thus far show the following are the areas in which robots score better than employees:

Accuracy: Employees often make basic data entry errors such as typing in DD/MM/YY instead of MM/DD/YY. Software doesn’t make such errors unless the underlying code is written incorrectly or the data is inconsistent. “Armies” of associates checking and correcting the work of other staff before a transaction is posted are not uncommon. RA eliminates the need for rework and releases productive capacity for meaningful work

24x7, uninterrupted labor: No shrinkage due to breaks, vacations, breaks, meetings, or employee attrition. RA can work around the clock as long as work and target systems are available

Flexibility: Processes often face volume spikes on defined (or sudden) days, weeks, months, and quarters during a year. Staffing tends to be sized to accommodate peak loads, with cost often to be paid for year-round. RA is modular and uses a lightweight deployment model, which makes it easy to replicate and ramp up or down the number of “robots” to meet the vagaries of demand, while maintaining optimal employee staffing

Compliance: Experienced associates tend to skip steps in the standard operating procedure (SOP) due to their experience, which can lead to errors. RA is programmed to always follow the SOP, and since there is as yet no self-learning mechanism, RA will keep on following it. This is an advantage especially in sensitive processes with regulatory oversight such as healthcare claims adjudication. In addition, the separate log-in IDs and passwords in RA mean transactions are segregated, enabling precise accountability between people and software. RA also generates extensive audit trails at the “keystroke” level, which provides an extra level of assurance during testing and production

The limits of RA

These advantages are fueling the “robotics” hype. What is the ultimate impact for all labor—be it business process optimization (BPO), shared services, or Global Business Services (GBS)—in the business process operations world? To understand the economic “end game,” we must analyze the significant limitations that apply.

Non-digital input type: RA products can’t read or extract data from scanned images without using OCR to extract the data. For many processes, the predominant input type is a scanned image, and consequently, an RA implementation would incur extra cost and implementation time to include OCR.

In some cases, the business case falls through because of this aspect. However, once the threshold of the early adoption curve is passed, and the default operating mode for a process changes to RA, we can theoretically expect a push for converting input types from digital images, such as a system-generated, structured .pdf, which can be easily read by robots. Again, the economic viability of these modifications depends on the cost of the respective IT implementation.

Diverse input formats: Process operations often see multiple formats from different vendors for invoices or even paper claims in health insurance. RA can be trained to read specific formats. Beyond a certain point, using multiple robots to read multiple formats becomes economically unviable to deploy and maintain. Unless RA providers inject their products with artificial intelligence, deploying robots to read different formats will always be a challenge. Attempting to influence vendors to submit inputs in a standard format would be difficult and time-consuming to implement. The organization might find it more appropriate to spend that effort nudging AP vendors toward electronic invoicing, which would eliminate human and robotic intervention.

Reading unstructured attachments and emails: Many interactions between process owners and associates happen via email, where instructions to process a certain exception are given. A free-flowing email is an unstructured data type and can’t be read by RA. Similarly, data arriving as an unstructured attachment, such as mortgage documents or supporting documents for healthcare claims, needs human intervention.

Take a copy for yourself

Download PDF

Complex exception handling and research: In some processes, straight-through processing happens without human touch, and only exceptions require human processing. The effort typically entails researching why the straight-through processing didn’t happen, obtaining additional approvals, and then posting the transaction manually. These actions require human understanding and become too complicated and expensive to be codified for RA.

SOP issues: RA is programmed based on the available SOPs for a process. The effectiveness of RA diminishes in processes that undergo frequent changes or for which the SOPs aren’t granular or comprehensive enough to cover many scenarios. In these cases, these would end up processing the simple parts of the transaction and flagging all others as exceptions requiring human intervention. In the case of frequent changes, this effort would require additional investment to change the coding, conduct testing, and redeploy the robot in the production environment. It could also lead to processing errors.

Other issues: Multiple scenarios exist where employees are required:

To read handwriting or verify signatures

A fraudster could mimic an invoice structure on plain paper and have it processed automatically. Employees would assess the authenticity of the document from its letterhead

The right approach to RA

This analysis has described the value and limitation of this fast-emerging, useful business process technology. There is no doubt that improved technologies will emerge over time and redefine the “art of the possible” in industrializing process operations through RA.

The RA landscape itself is rapidly evolving, and the ability to test usability across multiple types of processes is an advantage, since RA allows users to understand the real value and complexity. As the leading business service provider, Genpact has a long and broad experience with multiple clients across different process types. The main insight drawn from this vast experience is that RA risks increasing automation of badly designed processes.

A better automation strategy uses a combination of:

Optimal process design “kits” to define the future state process

Lean value-stream maps to identify and eliminate wasteful spend on non-value-added steps in the process

RA to provide the multiplier effect of process automation. Although this approach may take slightly longer to execute compared to quick-fix automation, it provides more sustainable benefits for client organizations

Visit our Digital Services

Sanjay Srivastava is Senior Vice President and Chief Digital Officer for Genpact. He is responsible for Genpact’s digital technology strategy and implementation, overseeing the software and services that the company provides to its clients – in key areas such as artificial intelligence (AI), robotic process automation (RPA), cognitive computing, dynamic workflow, data analytics, and mobility.